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On page 1719 (DOI: 10.1002/jcc.23949), X. W. Zhou, D. K. Ward, and M. E. Foster present a new parameterization of Pettifor's bond order potential for carbon, enabling direct molecular dynamics simulations of graphene growth on copper. In the image, the big bronze balls are copper atoms, red small balls are carbon atoms in an initial graphene island, and small blue balls are deposited carbon atoms. Traces of some selected depositing carbon atoms are shown by small gray balls at time-resolved locations. Without any assumptions regarding the graphene structures, other than the random addition of carbon adatoms, MD simulations have enabled high fidelity studies of defect formation during graphene growth.

A new parameterization of Pettifor's bond order potential has been performed for carbon. The method captures the property trends of important carbon phases and passes stringent molecular dynamics simulation tests: not only allowing for the crystalline growth of graphene, graphite, and carbon nanotubes, but also the transformation of graphite to diamond at high pressure.

CYP19A1 aromatase is a Cytochrome P450 responsible for the final step of the androgens conversion into the corresponding estrogens, and thus can play a significant role in the hormone-dependent breast cancer development. The first of three oxidative subcycles of this enzyme consists of an initial hydrogen abstraction followed by an oxygen rebound step, giving place to a hydroxylated form of the androstenedione substrate via two possible electronic spin pathways.

The 2D-Discrete Fourier Transform is introduced as a strategy for creating a common base to construct multivariate images for chemical structures using their magnitude spectra. Thus, for the first time, the modeling of structurally diverse noncongruent chemical images in the Multivariate Image Analysis-Quantitative Structure Activity Relationship context is possible.

A versatile high-accuracy computational scheme for the 77Se NMR chemical shifts of the medium-sized organoselenium compounds is suggested within a framework of a full four-component relativistic density functional theory. The main accuracy factors (functionals, basis sets, relativistic geometry, vibrational corrections, and solvent effects) are addressed.

M05-2X, M06-2X, M11-L, and N12 significantly underestimate the strengths of the adsorption of aromatic molecules on graphene. The best performing functionals are B97-D, B-LYP-D3, and ωB97X-D. The combination of SCS-SAPT0 and aug-cc-pVDZ performs very well for the energy component analysis of the adsorption of aromatic molecules on graphene.

The ASyncRE methodology is presented, allowing the performance of large-scale replica exchange molecular dynamics (REMD) simulations asynchronously on grid computing networks consisting of heterogeneous and distributed computing environments, as well as on homogeneous high performance clusters like NSF XSEDE clusters and BOINC distributed computing networks at Temple University and Brooklyn College at CUNY. Several ways to improve the efficiency of REMD simulations in the context of the ASyncRE methodology are also proposed.